# ewcdf: Weighted Empirical Cumulative Distribution Function In spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

## Description

Compute a weighted version of the empirical cumulative distribution function.

## Usage

 `1` ```ewcdf(x, weights = rep(1/length(x), length(x))) ```

## Arguments

 `x` Numeric vector of observations. `weights` Numeric vector of non-negative weights for `x`.

## Details

This is a modification of the standard function `ecdf` allowing the observations `x` to have weights.

The weighted e.c.d.f. (empirical cumulative distribution function) `Fn` is defined so that, for any real number `y`, the value of `Fn(y)` is equal to the total weight of all entries of `x` that are less than or equal to `y`. That is `Fn(y) = sum(weights[x <= y])`.

Thus `Fn` is a step function which jumps at the values of `x`. The height of the jump at a point `y` is the total weight of all entries in `x` number of tied observations at that value. Missing values are ignored.

If `weights` is omitted, the default is equivalent to `ecdf(x)` except for the class membership.

The result of `ewcdf` is a function, of class `"ewcdf"`, inheriting from the classes `"ecdf"` and `"stepfun"`. The class `ewcdf` has methods for `print` and `quantile`. The inherited class `ecdf` has methods for `plot` and `summary`.

## Value

A function, of class `"ewcdf"`, inheriting from `"ecdf"` and `"stepfun"`.

## Author(s)

\spatstatAuthors

.

`ecdf`.

`quantile.ewcdf`

## Examples

 ```1 2 3``` ``` x <- rnorm(100) w <- runif(100) plot(ewcdf(x,w)) ```

### Example output

```Loading required package: nlme